---
title: "dashboard"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    source: embed
---
```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(plotly)
library(p8105.datasets)

data("ny_noaa")
```

```{r}
# Limit the weather data to 2000 from the main data set
# Data cleaning; select observations with non-zero snowfalls and also limit to 200 snowfall.
ny_noaa_df= 
  ny_noaa %>%
  janitor::clean_names() %>%
  drop_na() %>%
  separate(col = date, into = c ("year", "month", "day") , sep = "-", convert = TRUE) %>%
  mutate(snowfall = snow*25.4,
         month = month.abb[month],
         tmax = as.numeric(tmax) / 10,
         tmin = as.numeric(tmin) / 10) %>%
  filter(snow > 0, snow < 200, year == 2000) %>%
  select(id, year, month, day, snowfall, tmax, tmin)
```

Column {data-width=650}
-----------------------------------------------------------------------

### Chart A: New York Station's Snowfalls in 2000

```{r}
ny_noaa_df %>% 
  mutate(month = fct_reorder(month, snowfall)) %>% 
  plot_ly(y = ~snowfall, color = ~month, type = "box", colors = "viridis") %>%
  layout(xaxis = list(title = 'Month'),
         yaxis = list(title = 'Snowfall (mm)'))
```


Column {data-width=350}
-----------------------------------------------------------------------

### Chart B: New York Station's Monthly Mininum and Maximum Temperature in 2000

```{r}

ny_noaa_df %>%
  plot_ly(x = ~tmin, y = ~tmax, color = ~month, opacity=0.5, colors = "viridis") %>%
  layout(xaxis = list(title = 'Mininum Temperature'),
         yaxis = list(title = 'Maximum Temperature'))

```

### Chart C: New York Station's Snowy Days Frequency in 2000

```{r}
ny_noaa_df %>% 
  count(id) %>% 
  mutate(id = fct_reorder(id, n)) %>% 
  plot_ly(x = ~id, y = ~n, color = ~id, type = "bar", colors = "viridis") %>%
  layout(xaxis = list(title = 'Weather station ID'),
         yaxis = list(title = 'Number Snowy Days'))


```
```